This research program seeks to contribute to the understanding of human behavior through a study of language. We assume that generative grammar describes an essential aspect of human capacity for language. Accordingly, we will focus on models of language users which are capable of accounting for the structural descriptions of sentences which generative gammars provide. These models will be developed and tested in three closely interrelated areas: sentence comprehension, sentence production, and first language learning. The processes underlying the production and comprehension of speech will be experimentally evaluated primarily in terms of their ability to account for the relative complexity and for the segmentation of sentences. We will assess complexity and segmentation factors by a variety of experimental techniques (for example, reaction times for detection of phonetic, lexical, and semantic features of sentences; the induction of speech errors under time stress or fatigue; the order of appearance of different sentence types in the comprehension and production repertoires of children). An overriding concern in all our experimentation will be an attempt to distinguish the role of phonetic, syntactic and semantic variables in language processing and language learning. In particular we will be concerned to experimentally disentangle the consequences of on-line sentence analysis from that of inference processes.